Description

You will manage end-to-end machine learning projects from inception through deployment, focusing on MLOps and automation.

Responsibilities

• Manage ML projects from inception to deployment using MLOps best practices.
• Develop models using TensorFlow, PyTorch, Keras, and Scikit-Learn.
• Implement MLOps tools including MLflow, Kubeflow, Pachyderm, and DVC for lifecycle management.
• Build scalable ML systems and integrate feature stores.
• Collaborate with cross-functional data science teams.

Required Skills

• 5+ years of experience in machine learning engineering.
• Proficiency with TensorFlow, PyTorch, Keras, and Scikit-Learn.
• Hands-on experience with MLflow, Kubeflow, Pachyderm, and DVC.
• Experience using Spark and Databricks.
• Strong understanding of MLOps practices and automation.
• Background in Statistics, Economics, Computer Science, Mathematics, or Operations Research.
• Degree in a relevant quantitative field.

Preferred Skills

• Familiarity with cloud platforms including AWS, Azure, or GCP.
• Experience with containerization technologies.
• Proficiency in implementing CI/CD pipelines for ML models.

Key Skills

Education

Any Graduate